Recall Isn't Enough: Bounding Commitments in Personalized Language Systems

In three linesarXiv paper introducing CBEA+LCV, a method for validating commitments in personalized language systems. Rather than treating personalization as recall, the approach structures constraints before generation. Across 360 fixtures, achieves zero failures at 0.49-0.60 availability versus 0.003-0.092 for baselines, with 74-75% payload reduction.

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